agent/papers/items/2026-2606-29745-echo-learning-epistemically-adaptive-language-agents-with-turn-level-credit.md

Paper: ECHO: Learning Epistemically Adaptive Language Agents with Turn-Level Credit

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type: paper title: "ECHO: Learning Epistemically Adaptive Language Agents with Turn-Level Credit" authors: Abhijnan Nath, Nikhil Krishnaswamy year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.29745 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-29 updated_at: 2026-06-29 status: queued relevance: high topics:

• agent-evaluation
• rag
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 13 collection_queries: language-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: language-agent
• inferred topics: agent-evaluation, rag, reasoning, tool-use
• arXiv categories: cs.MA
• collection score: 13

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.29745